A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
Machine learning: an advanced platform for materials development and state prediction in lithium‐ion batteries
Lithium‐ion batteries (LIBs) are vital energy‐storage devices in modern society. However,
the performance and cost are still not satisfactory in terms of energy density, power density …
the performance and cost are still not satisfactory in terms of energy density, power density …
Lithium-ion battery capacity and remaining useful life prediction using board learning system and long short-term memory neural network
S Zhao, C Zhang, Y Wang - Journal of Energy Storage, 2022 - Elsevier
In order for lithium-ion batteries to function reliably and safely, accurate capacity and
remaining useful life (RUL) predictions are essential, but challenging. Some current deep …
remaining useful life (RUL) predictions are essential, but challenging. Some current deep …
[HTML][HTML] A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles
With electric vehicles (EVs) being widely accepted as a clean technology to solve carbon
emissions in modern transportation, lithium-ion batteries (LIBs) have emerged as the …
emissions in modern transportation, lithium-ion batteries (LIBs) have emerged as the …
[HTML][HTML] A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery
Lithium-ion batteries are used in a wide range of applications including energy storage
systems, electric transportations, and portable electronic devices. Accurately obtaining the …
systems, electric transportations, and portable electronic devices. Accurately obtaining the …
A review of deep learning approach to predicting the state of health and state of charge of lithium-ion batteries
In the field of energy storage, it is very important to predict the state of charge and the state of
health of lithium-ion batteries. In this paper, we review the current widely used equivalent …
health of lithium-ion batteries. In this paper, we review the current widely used equivalent …
Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling
Designing and deployment of state-of-the-art electric vehicles (EVs) in terms of low cost and
high driving range with appropriate reliability and security are identified as the key towards …
high driving range with appropriate reliability and security are identified as the key towards …
Review on state-of-health of lithium-ion batteries: Characterizations, estimations and applications
Abstract State-of-health (SOH) monitoring of lithium-ion batteries plays a key role in the
reliable and safe operation of battery systems. Influenced by multiple factors, SOH is an …
reliable and safe operation of battery systems. Influenced by multiple factors, SOH is an …
A data-driven auto-CNN-LSTM prediction model for lithium-ion battery remaining useful life
Integration of each aspect of the manufacturing process with the new generation of
information technology such as the Internet of Things, big data, and cloud computing makes …
information technology such as the Internet of Things, big data, and cloud computing makes …
Integration of energy storage system and renewable energy sources based on artificial intelligence: An overview
Energy storage technology plays a role in improving new energy consumption capacities,
ensuring the stable and economic operation of power systems, and promoting the …
ensuring the stable and economic operation of power systems, and promoting the …